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Architectural Tactics to Optimize Software for Energy Efficiency in the Public Cloud

Authors: Vos S.; Lago P.; Verdecchia R.; Heitlager I.;

Architectural Tactics to Optimize Software for Energy Efficiency in the Public Cloud

Abstract

A promise of cloud computing is the reduction of energy footprint enabled by economies of scale. Unfortunately, little research is available on how cloud consumers can reduce their energy footprint when running software in the public cloud. Moreover, cloud consumers do not have full access to information regarding their cloud infrastructure usage, which is required to understand the impact of design decisions on energy usage. The purpose of our study is to support cloud consumers in developing energy-efficient workloads in the public cloud. To achieve our goal, we collaborated with a large cloud solution provider to discover an initial set of reusable architectural tactics for software energy efficiency. Starting from interviews with 17 practitioners, we reviewed and selected available tactics to improve the energy efficiency of individual workloads in the public cloud, and synthetized the identified tactics in a reusable model. In addition, we conducted a case study to assess the impact of utilizing a tactic, which was selected following a prioritization provided by the practitioners. Our results demonstrate the possibility to architect cloud workloads for energy efficiency through reasoning and estimation of resource optimization. However, the process is not (yet) straightforward due to the current lack of transparency of cloud providers.

Countries
Italy, Netherlands, Netherlands
Keywords

Energy Efficiency, Edge Computing; Energy Efficiency; Public Cloud; Software Architecture; Tactics, Software Architecture, and Infrastructure, Edge Computing, Connected World, Science for Sustainability, Innovation, SDG 12 - Responsible Consumption and Production, Public Cloud, SDG 9 - Industry, Tactics

  • BIP!
    Impact byBIP!
    citations
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    8
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 10%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%